Understand how a treatment behaves before it reaches the lab. LURA models how compounds move through tumor tissue and how patients differ, so you can decide what to advance and what to stop early.
Bring us the decision you can't makeFor drug development teams at pharma, biotech and CROs.
A portfolio in. A field compiled. A picture you can defend.
Roughly nine in ten drugs that enter clinical trials never reach approval. By then, years of research and substantial capital may already be committed.
Laboratory results can tell us a great deal about a compound. They cannot fully account for the conditions it will encounter in living tissue.
Understanding that behavior earlier could change which experiments we run, which compounds we advance, and where we invest our time.
Drug–cell pairs screened: 2.5 million interactions in 1.5 seconds on a single NVIDIA A100. Test conditions are shared in a technical evaluation.
LURA is a high-throughput, biophysics-driven tissue simulator. You bring the portfolio and it answers in seconds. A program you stop early gives back its months and millions while they still matter.
Not one molecule at a time.
Not one cell line, one afternoon.
On the same page, each labelled for what it is.
Which compounds win in which genotype, and whether they reach the cells that matter.
Whether the payload reaches the cells the antibody never touched.
Predicted exposure across a simulated population, so biological variability stays in the answer.
With the reasons attached, and the disagreements kept, not averaged away.
Both auditable by your own scientists.
A compound cannot work where it never arrives.
Tissue pharmacology models how far a drug penetrates, how much of the tissue it covers, and how the tissue responds.
From a solved tissue model, not a measurement. Every result says which.
In a well, every cell sits at zero distance from the drug. In a tumor it has to travel. The outer layers get treated. The core never sees a dose.
Oxygen, acidity and pressure change across a mass, and each changes what a drug does. One compound, two answers.
The share of the tumor at a therapeutic dose, the regions that never get one, by name, and how that share shifts from one virtual patient to the next. A named failure is a design brief. An averaged one is a surprise in year three.
Deprioritize it before the animal study, with the tissue reason attached.
Compounds ranked by selectivity in each genetic context.
A labelled estimate with a range. Never dropped, never dressed up as a measurement.
The direction of the answer, with its sensitivity printed beside it.
Every number with its evidence, assumptions and limits, so a reviewer can challenge it.
A sealed record you can reopen and defend a year later.
In a retrospective test, EGFR inhibitors ranked hundreds of times more selective than controls in an EGFR-mutant line. BRAF inhibitors did the same in a BRAF-mutant line. A line with no targetable driver showed no signal.
A computational answer nobody can challenge is not evidence. It is an assertion with arithmetic attached. So every LURA result carries its benchmark, the assumptions under it, its uncertainty, and what is still unknown, and it can be reopened and audited by your own scientists. A direct measurement never reads like an inferred one.
Private technical evaluations, scientific collaborations and institutional partnerships.
A good first evaluation is a program you have already closed. We run it and show you where LURA agrees with your bench result and where it does not.
Relevant technical information is shared through a qualified process.
A new way to investigate living systems.
Elyris builds computational tools that show how a treatment behaves inside living tissue, beginning with tumors. The ambition is long. What we claim stays with what LURA demonstrably does today, and every result says what it is.
The people behind it.
About Elyris Labs